Predicting the potential demographic impact of predators on their prey: a comparative analysis of two carnivore-ungulate systems in Scandinavia

Abstract

1. Understanding the role of predation in shaping the dynamics of animal communities is a fundamental issue in ecological research. Nevertheless, the complex nature of predator-prey interactions often prevents researchers from modelling them explicitly. 2. By using periodic Leslie-Usher matrices and a simulation approach together with parameters obtained from long-term field projects, we reconstructed the underlying mechanisms of predator-prey demographic interactions and compared the dynamics of the roe deer-red fox-Eurasian lynx-human harvest system with those of the moose-brown bear-gray wolf-human harvest system in the boreal forest ecosystem of the southern Scandinavian Peninsula. 3. The functional relationship of both roe deer and moose λ to changes in predation rates from the four predators was remarkably different. Lynx had the strongest impact among the four predators, whereas predation rates by wolves, red foxes, or brown bears generated minor variations in prey population λ. Elasticity values of lynx, wolf, fox and bear predation rates were -0·157, -0·056, -0·031 and -0·006, respectively, but varied with both predator and prey densities. 4. Differences in predation impact were only partially related to differences in kill or predation rates, but were rather a result of different distribution of predation events among prey age classes. Therefore, the age composition of killed individuals emerged as the main underlying factor determining the overall per capita impact of predation. 5. Our results confirm the complex nature of predator-prey interactions in large terrestrial mammals, by showing that different carnivores preying on the same prey species can exert a dramatically different demographic impact, even in the same ecological context, as a direct consequence of their predation patterns. Similar applications of this analytical framework in other geographical and ecological contexts are needed, but a more general evaluation of the subject is also required, aimed to assess, on a broader systematic and ecological range, what specific traits of a carnivore are most related to its potential impact on prey species.

Fig. 1

Structural diagram illustrating the demographic processes leading to the observed growth rate in prey populations, decomposed into three levels of increasing detail. Level 1 includes the effect of main demographic rates (age-specific survival, recruitment); in level 2, individual survival is decomposed into its basic mechanisms, that is, the main age-specific mortality factors (predation rate, harvest rate, natural mortality rate); in level 3, age-specific predation rate is decomposed into its basic mechanisms, that is, kill rate, predator density, prey density and age class of killed individuals.

Fig. 2

Descriptive statistics of Eurasian lynx, gray wolf, brown bear and red fox predation patterns on roe deer and moose in Scandinavia. Functional response curves (a) and age distribution of killed individuals (b) are shown. One radio-monitored adult roe deer has been killed by red fox in our study area (J.D.C. Linnell pers. comm.). However, given the insignificant demographic impact, we disregarded red fox as a predator for adult roe deer.

Fig. 3

Effects of changes in predation and harvest rates of Eurasian lynx, gray wolves, brown bears, red fox and hunters on roe deer and moose population growth rate in Scandinavia, resulting from a multi-level periodic matrix model of their demography. Estimates are based on baseline densities of 0·57 and 1·00 individuals per km² for roe deer and moose, respectively, and 0·4, 0·5 and 1·0 individuals per 100 km² for lynx, wolf and bear, respectively. No initial density estimate was available for the red fox.

Fig. 4

Effect of changes in prey density on the elasticity of moose and roe deer λ to Eurasian lynx, gray wolf, red fox and brown bear predation rates in Scandinavia. Baseline densities for roe deer and moose populations in the study area are 0·57 and 1·00 individuals per km², respectively.

Fig. 5

Relationship between changes in lower-level predation parameters of Eurasian lynx, gray wolf, brown bear and red fox, and the resulting projected growth rate of roe deer and moose populations in Scandinavia. The effects of changes in predator density (a), per capita kill rate (b) and predator selectivity for adult individuals (c) are shown. Points without CI bars on each line represent the baseline age selection index for each predator. Baseline densities for roe deer and moose populations in the study area are 0·57 and 1·00 individuals per km², respectively, whereas for lynx, wolf and brown bear populations, they are 0·4, 0·5 and 1·0 individuals per 100 km², respectively.

Fig. 6

Barplot of elasticity values associated with all demographic and predation parameters, as resulting from a multi-level periodic matrix model of roe deer and moose demography in Scandinavia. Estimates are based on baseline densities of 0·57 and 1·00 individuals per km² for roe deer and moose, respectively, and 0·4, 0·5, and 1·0 individuals per 100 km² for lynx, wolf and bear, respectively.